diff --git a/CHANGELOG.md b/CHANGELOG.md index d8bb7cbf4a6..39ddd9bfd55 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -37,6 +37,7 @@ Also, that release drops support for Python 3.9, making Python 3.10 the minimum * Added support for the `out` keyword to accept a tuple, bringing ufunc signatures into alignment with those in NumPy [#2664](https://github.com/IntelPython/dpnp/pull/2664) * Unified public API definitions in `dpnp.linalg` and `dpnp.scipy` submodules [#2663](https://github.com/IntelPython/dpnp/pull/2663) * Aligned the signature of `dpnp.reshape` function with Python array API by making `shape` a required argument [#2673](https://github.com/IntelPython/dpnp/pull/2673) +* Disallowed conversion of `dpnp.ndarray` with more than one dimension to Python scalars (`int`, `float`, `complex`) to align with NumPy 2.4.0 [#2694](https://github.com/IntelPython/dpnp/pull/2694) ### Deprecated diff --git a/dpnp/dpnp_array.py b/dpnp/dpnp_array.py index 3148e7757f6..0f11a84b6c6 100644 --- a/dpnp/dpnp_array.py +++ b/dpnp/dpnp_array.py @@ -196,6 +196,7 @@ def __bytes__(self): def __complex__(self, /): """Convert a zero-dimensional array to a Python complex object.""" + self._check_scalar_convertible() return self._array_obj.__complex__() def __contains__(self, value, /): @@ -302,6 +303,7 @@ def __eq__(self, other, /): def __float__(self, /): """Convert a zero-dimensional array to a Python float object.""" + self._check_scalar_convertible() return self._array_obj.__float__() def __floordiv__(self, other, /): @@ -393,6 +395,7 @@ def __index__(self, /): def __int__(self, /): """Convert a zero-dimensional array to a Python int object.""" + self._check_scalar_convertible() return self._array_obj.__int__() def __invert__(self, /): @@ -610,6 +613,14 @@ def __xor__(self, other, /): r"""Return :math:`\text{self ^ value}`.""" return dpnp.bitwise_xor(self, other) + def _check_scalar_convertible(self): + """Raise if array cannot be converted to a Python scalar.""" + if self.ndim != 0: + raise TypeError( + "Only 0-dimensional dpnp.ndarray can be converted " + "to a Python scalar" + ) + @staticmethod def _create_from_usm_ndarray(usm_ary: dpt.usm_ndarray): """ diff --git a/dpnp/tests/test_ndarray.py b/dpnp/tests/test_ndarray.py index c7e9dc65b99..6721f0f7a8d 100644 --- a/dpnp/tests/test_ndarray.py +++ b/dpnp/tests/test_ndarray.py @@ -5,6 +5,7 @@ assert_allclose, assert_array_equal, assert_equal, + assert_raises, assert_raises_regex, ) @@ -17,6 +18,7 @@ get_complex_dtypes, get_float_dtypes, has_support_aspect64, + numpy_version, ) from .third_party.cupy import testing @@ -530,34 +532,53 @@ def test_print_dpnp_zero_shape(): assert result == expected -# Numpy will raise an error when converting a.ndim > 0 to a scalar -# TODO: Discuss dpnp behavior according to these future changes -@pytest.mark.filterwarnings("ignore::DeprecationWarning") -@pytest.mark.parametrize("func", [bool, float, int, complex]) +@pytest.mark.parametrize("xp", [dpnp, numpy]) @pytest.mark.parametrize("shape", [tuple(), (1,), (1, 1), (1, 1, 1)]) -@pytest.mark.parametrize( - "dtype", get_all_dtypes(no_float16=False, no_complex=True) -) -def test_scalar_type_casting(func, shape, dtype): - a = numpy.full(shape, 5, dtype=dtype) - ia = dpnp.full(shape, 5, dtype=dtype) - assert func(a) == func(ia) +class TestPythonScalarConversion: + @pytest.mark.parametrize( + "dtype", get_all_dtypes(no_none=True, no_float16=False, no_complex=True) + ) + def test_bool_conversion(self, xp, shape, dtype): + a = xp.full(shape, 5, dtype=dtype) + assert bool(a) == True + @pytest.mark.parametrize( + "dtype", get_all_dtypes(no_none=True, no_float16=False, no_complex=True) + ) + def test_bool_method_conversion(self, xp, shape, dtype): + a = xp.full(shape, 5, dtype=dtype) + assert a.__bool__() == True -# Numpy will raise an error when converting a.ndim > 0 to a scalar -# TODO: Discuss dpnp behavior according to these future changes -@pytest.mark.filterwarnings("ignore::DeprecationWarning") -@pytest.mark.parametrize( - "method", ["__bool__", "__float__", "__int__", "__complex__"] -) -@pytest.mark.parametrize("shape", [tuple(), (1,), (1, 1), (1, 1, 1)]) -@pytest.mark.parametrize( - "dtype", get_all_dtypes(no_float16=False, no_complex=True) -) -def test_scalar_type_casting_by_method(method, shape, dtype): - a = numpy.full(shape, 4.7, dtype=dtype) - ia = dpnp.full(shape, 4.7, dtype=dtype) - assert_allclose(getattr(a, method)(), getattr(ia, method)(), rtol=1e-06) + @testing.with_requires("numpy>=2.4") + @pytest.mark.parametrize("func", [float, int, complex]) + @pytest.mark.parametrize( + "dtype", get_all_dtypes(no_none=True, no_float16=False, no_complex=True) + ) + def test_non_bool_conversion(self, xp, func, shape, dtype): + a = xp.full(shape, 5, dtype=dtype) + if len(shape) > 0: + # Non-0D arrays must not be convertible to Python numeric scalars + assert_raises(TypeError, func, a) + else: + # 0D arrays are allowed to convert + expected = 1 if dtype == xp.bool else 5 + assert func(a) == func(expected) + + @testing.with_requires("numpy>=2.4") + @pytest.mark.parametrize("method", ["__float__", "__int__", "__complex__"]) + @pytest.mark.parametrize( + "dtype", get_all_dtypes(no_none=True, no_float16=False, no_complex=True) + ) + def test_non_bool_method_conversion(self, xp, method, shape, dtype): + a = xp.full(shape, 5, dtype=dtype) + if len(shape) > 0: + assert_raises(TypeError, getattr(a, method)) + else: + expected = 1 if dtype == xp.bool else 5 + func = {"__float__": float, "__int__": int, "__complex__": complex}[ + method + ] + assert getattr(a, method)() == func(expected) @pytest.mark.parametrize("shape", [(1,), (1, 1), (1, 1, 1)])